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Data Analysis with R Programming · LearnSpace
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Data Analysis with R Programming

Курс от Google
Начальный≈ 31.7 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

This course is the seventh course in the Google Data Analytics Certificate. In this course, you’ll learn about the programming language known as R. You’ll find out how to use RStudio, the environment that allows you to work with R, and the software applications and tools that are unique to R, such as R packages. You’ll discover how R lets you clean, organize, analyze, visualize, and report data in new and more powerful ways. Current Google data analysts will continue to instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources. Learners who complete this certificate program will be equipped to apply for introductory-level jobs as data analysts. No previous experience is necessary. By the end of this course, learners will: - Examine the benefits of using the R programming language. - Discover how to use RStudio to apply R to your analysis. - Explore the fundamental concepts associated with programming in R. - Understand the contents and components of R packages including the Tidyverse package. - Gain an understanding of dataframes and their use in R. - Discover the options for generating visualizations in R. - Learn about R Markdown for documenting R programming.

Навыки, которые вы освоите

R ProgrammingData ManipulationGgplot2RmarkdownData AnalysisData CleansingTidyverse (R Package)Development EnvironmentStatistical ReportingData Visualization SoftwareProgramming PrinciplesStatistical VisualizationStatistical ProgrammingPlot (Graphics)Data VisualizationData WranglingR (Software)

Программа курса

5 модулей · 118 учебных материалов

01Programming and data analytics22 материалов

The exciting world of programming

Introduction to the exciting world of programmingВидеоCourse syllabusЧтениеHelpful resources and tipsЧтениеThe R-versus-Python debateЧтение

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Преподаватель курса

Data Analysis with R Programming
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Обучение на Coursera

≈ 31.7 ч

5 модулей

Язык: Английский

Субтитры: Арабский, Французский, Украинский, Бразильский португальский, Корейский, Немецкий, Индонезийский, Турецкий, Испанский, Японский

Часть программы вашего университета
Learning Log: Get ready to explore RЧтение
Fun with RВидео
Carrie: Getting started with RВидео

Programming as a data analyst

Programming languagesВидеоWays to learn about programmingЧтениеFrom spreadsheets to SQL to RЧтениеIntroduction to R ВидеоOptional Hands-On Activity: Downloading and installing RЗаданиеOptional Hands-On Activity: R ConsoleЗаданиеTest your knowledge on programming languagesЗадание

Learn programming using RStudio

Intro to RStudio ВидеоHands-On Activity: Cloud access to RStudioЗаданиеOptional Hands-On Activity: Get started in RStudio DesktopЗаданиеWhen to use RStudioЧтениеConnect with other analysts in the R communityЧтениеTest your knowledge on programming with RStudioЗадание

Module 1 challenge

Glossary terms from module 1ЧтениеModule 1 challengeЗадание
02Programming using RStudio24 материалов

Understand basic programming concepts

Programming using RStudioВидеоProgramming fundamentalsВидеоVectors and lists in RЧтениеDates and times in RЧтениеOther common data structuresЧтениеTest your knowledge on programming conceptsЗадание

Explore coding in R

Operators and calculationsВидеоLogical operators and conditional statementsЧтениеGuide: Keeping your code readable ЧтениеHands-On Activity: R sandboxЗаданиеBasic Concepts of RPLUGINTest your knowledge on coding in RЗадание

Learning about R packages

The gift that keeps on givingВидеоAvailable R packages ЧтениеWelcome to the tidyverseВидеоHands-On Activity: Installing and loading tidyverseЗаданиеTest your knowledge on R packages Задание

Explore the tidyverse

More on the tidyverse ВидеоUse pipes to nest codeВидеоR resources for more helpЧтениеConnor: Coding tipsВидеоTest your knowledge on the tidyverseЗадание

Module 2 challenge

Glossary terms from module 2ЧтениеModule 2 challengeЗадание
03Working with data in R 25 материалов

Explore data and R

Data in R ВидеоR data frames ВидеоWorking with data framesВидеоHands-on Activity: Create your own data frameЗаданиеMore about tibblesЧтениеData-import basicsЧтениеHands-On Activity: Importing and working with dataЗаданиеTest your knowledge on R data framesЗадание

Cleaning data

Cleaning up with the basics ВидеоFile-naming conventionsЧтениеMore on R operatorsЧтениеOrganize your dataВидеоHands-On Activity: Cleaning data in R ЗаданиеOptional: Manually create a data frame ЧтениеTransforming data

Take a closer look at the data

Same data, different outcomeВидеоThe bias functionВидеоWork with biased dataЧтениеHands-On Activity: Changing your dataЗаданиеTest your knowledge on R functionsЗадание

Module 3 challenge

Glossary terms from module 3 ЧтениеModule 3 challengeЗадание
04More about visualizations, aesthetics, and annotations 26 материалов

Create data visualizations in R

Visualizations in RВидеоVisualization basics in R and tidyverseВидеоHands-On Activity: Visualizing data with ggplot2ЗаданиеGetting started with ggplot()ВидеоCommon problems when visualizing in RЧтениеHands-On Activity: Using ggplotЗаданиеJoseph: Career path to people analyticsВидеоTest your knowledge on data visualizations in RЗадание

Explore aesthetics in analysis

Enhancing visualizations in RВидеоAesthetic attributesЧтениеDoing more with ggplotВидеоSmoothingЧтениеAesthetics and facetsВидеоHands-On Activity: Aesthetics and visualizations ЗаданиеFilters and plots

Annotate and save visualizations

Annotation layer ВидеоAdding annotations in RЧтениеSaving your visualizationsВидеоSaving images without ggsave()ЧтениеHands-On Activity: Annotating and saving visualizationsЗаданиеTest your knowledge on annotating and saving visualizationsЗадание

Module 4 challenge

Glossary terms from module 4ЧтениеModule 4 challengeЗадание
05Documentation and reports21 материалов

Develop documentation and reports in RStudio

Documentation and reportsВидеоOverview of R MarkdownВидеоR Markdown resourcesЧтениеOptional: Jupyter notebooksЧтениеUsing R Markdown in RStudioВидеоHands-On Activity: Your R Markdown notebookЗаданиеTest your knowledge about documentation and reportsЗадание

Create R Markdown documents

Structure of markdown documentsВидеоMeg: Programming is empoweringВидеоEven more document elementsВидеоTest your knowledge about creating R Markdown documentsЗадание

Understand code chunks and exports

Code chunksВидеоHands-On Activity: Adding code chunks to R Markdown notebooksЗаданиеExporting documentationВидеоOutput formats in R MarkdownЧтениеHands-On Activity: Exporting your R Markdown notebookЗаданиеTest your knowledge on code chunks Задание

Module 5 challenge

Glossary: Terms and definitionsЧтениеModule 5 challengeЗадание

Course wrap-up

Reflect and connect with peersЧтениеComing up next...Чтение
Видео
Wide to long with tidyrЧтение
Clean, organize, and transform data with RPLUGIN
Test your knowledge on cleaning data Задание
Чтение
Hands-On Activity: Filters and plotsЗадание
Elements of ggplotPLUGIN
Test your knowledge on aesthetics in analysis Задание